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The Impact of Artificial Intelligence on Waiting Time for Medical Care in an Urgent Care Service for COVID-19: Single-Center Prospective Study.
Bin, Kaio Jia; Melo, Adler Araujo Ribeiro; da Rocha, José Guilherme Moraes Franco; de Almeida, Renata Pivi; Cobello Junior, Vilson; Maia, Fernando Liebhart; de Faria, Elizabeth; Pereira, Antonio José; Battistella, Linamara Rizzo; Ono, Suzane Kioko.
  • Bin KJ; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Melo AAR; Department of Internal Medicine, Federal University of Sao Paulo, Sao Paulo, Brazil.
  • da Rocha JGMF; Escola de Engenharia de Sao Carlos, Universidade de Sao Paulo, Sao Carlos, Brazil.
  • de Almeida RP; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Cobello Junior V; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Maia FL; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • de Faria E; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Pereira AJ; Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Battistella LR; Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
  • Ono SK; Department of Gastroenterology, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.
JMIR Form Res ; 6(2): e29012, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1662500
ABSTRACT

BACKGROUND:

To demonstrate the value of implementation of an artificial intelligence solution in health care service, a winning project of the Massachusetts Institute of Technology Hacking Medicine Brazil competition was implemented in an urgent care service for health care professionals at Hospital das Clínicas of the Faculdade de Medicina da Universidade de São Paulo during the COVID-19 pandemic.

OBJECTIVE:

The aim of this study was to determine the impact of implementation of the digital solution in the urgent care service, assessing the reduction of nonvalue-added activities and its effect on the nurses' time required for screening and the waiting time for patients to receive medical care.

METHODS:

This was a single-center, comparative, prospective study designed according to the Public Health England guide "Evaluating Digital Products for Health." A total of 38,042 visits were analyzed over 18 months to determine the impact of implementing the digital solution. Medical care registration, health screening, and waiting time for medical care were compared before and after implementation of the digital solution.

RESULTS:

The digital solution automated 92% of medical care registrations. The time for health screening increased by approximately 16% during the implementation and in the first 3 months after the implementation. The waiting time for medical care after automation with the digital solution was reduced by approximately 12 minutes compared with that required for visits without automation. The total time savings in the 12 months after implementation was estimated to be 2508 hours.

CONCLUSIONS:

The digital solution was able to reduce nonvalue-added activities, without a substantial impact on health screening, and further saved waiting time for medical care in an urgent care service in Brazil during the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: JMIR Form Res Year: 2022 Document Type: Article Affiliation country: 29012

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: JMIR Form Res Year: 2022 Document Type: Article Affiliation country: 29012